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Home»News»Ultra-selective aptamers give viruses a taste of their own medicine
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Ultra-selective aptamers give viruses a taste of their own medicine

June 18, 2025No Comments4 Mins Read
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Ultra-selective aptamers give viruses a taste of their own medicine
Illustration of the Multivalent Evolved DNA-based SUpramolecular Assemblies (MEDUSA), shown in white, interacting with a target protein (pink). Credit: 2025 PBL EPFL CC BY SA 4.0

Inspired by the way viruses attach to cells, EPFL scientists have developed a method for engineering ultra-selective aptamers.

Aptamers are short segments of DNA or RNA that are designed to bind, like antibodies, to specific targets. Synthetic and inexpensive to produce, aptamers are attractive alternatives to antibodies for biomedical diagnostics and therapeutics.

When new aptamer binders are needed, for example, to detect a new virus, they are developed from libraries of millions of nucleic acid sequences from which the best matches for a given target are selected and amplified.

Until now, such libraries contained only monovalent binders: sequences that bind to one site on a target molecule. But this contrasts with the structure of many real-world proteins, including the SARS-CoV-2, influenza, and HIV spike proteins. These structures, which viruses use to infect cells, are comprised of three identical subunits presenting three potential binding sites.

Unfortunately, using monovalent binders for these three-unit (trimeric) complexes is hit-or-miss. In fact, Maartje Bastings, head of the Programmable Biomaterials Lab in EPFL’s School of Engineering, compares it to “throwing a bowl of spaghetti at the wall, as ‘something’ will certainly stick ‘somewhere.'”

Bastings explains, “You can’t control where a monovalent binder interacts with its target: for example, it may bind to the side of a protein, rather than the binding interface, reducing its functionality. In other words, you can’t choose the spot on the wall where a certain spaghetti noodle will stick. So, we thought: wouldn’t it be better to pre-organize our library for binders that fit a target’s exact geometry? And this approach turns out to be magically effective.”

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Bastings and her team report the first technique for producing multimeric aptamers, which target protein complexes with unprecedented precision and functionality. The binders developed with the lab’s approach, dubbed MEDUSA (Multivalent Evolved DNA-based SUpramolecular Assemblies), yield binding affinities that are between 10 and 1,000 times stronger than those achieved with monovalent binders. In addition to being stronger, they also turned out to be much more selective, which is critical for diagnostics.

The research has been published in Nature Nanotechnology.

A bioinspired approach

The key to developing trimeric binders is the scaffold: a molecular structure around which three binding units naturally assemble. In their experiments, the researchers developed their scaffold based on the geometry of the SARS-CoV-2 spike protein.

By adding these tailored scaffolds to their aptamer library, the team was able to bias the sequence space toward trimeric candidates that would bind functionally to the target interface right from the start.

“We have retro-engineered the natural paradigm seen in viruses, in which multivalent molecular complexes co-evolve, and translated it into a new binder discovery method that allows us to select multivalent binders that can block such viruses,” summarizes Ph.D. student and first author Artem Kononenko.

Once a first batch of binders is identified, candidates with increasing affinity for their target are developed through an iterative process of selection and amplification called “evolution.”

Although designing new scaffolds can take a matter of hours, the evolution process can take weeks. Looking ahead, the research team aims to shorten this timeframe to better suit the needs of biomedical diagnostics and therapeutics.

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Another goal is to develop multimeric binders targeting pathogens with even more complex configurations, like Dengue fever (six binding subunits) or anthrax (seven).

“Ultimately, we want to use this new multivalent sequence space to train generative artificial intelligence models to do this for us,” Bastings says.

Provided by
Ecole Polytechnique Federale de Lausanne



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